CD4(+) T cell-dependent and CD4(+) T cell-independent cytokine-chemokine network changes in the immune responses of HIV-infected individuals

TitleCD4(+) T cell-dependent and CD4(+) T cell-independent cytokine-chemokine network changes in the immune responses of HIV-infected individuals
Publication TypeJournal Article
Year of Publication2015
AuthorsArnold, KB, Szeto, GL, Alter, G, Irvine, DJ, Lauffenburger, DA
JournalScience Signaling
Volume8
Issue399
Paginationra104
Date Published2015/10/20/
Abstract

A vital defect in the immune systems of HIV-infected individuals is the loss of CD4(+) T cells, resulting in impaired immune responses. We hypothesized that there were CD4(+) T cell-dependent and CD4(+) T cell-independent alterations in the immune responses of HIV-1(+) individuals. To test this, we analyzed the secretion of cytokines and chemokines from stimulated peripheral blood mononuclear cell (PBMC) populations from HIV+ donors, healthy donors, and healthy donors with CD4(+) T cells experimentally depleted. Multivariate analyses of 16 cytokines and chemokines at 6 and 72 hours after three stimuli (antibody-coated beads to stimulate T cells and R848 or lipopolysaccharide to stimulate innate immune cells) enabled integrative analysis of secreted profiles. Two major effects in HIV+ PBMCs were not reproduced upon depletion of CD4(+) T cells in healthy PBMCs: (i) HIV+ PBMCs maintained T cell-associated secreted profiles after T cell stimulation; (ii) HIV+ PBMCs showed impaired interferon-gamma (IFN-gamma) secretion early after innate stimulation. These changes arose from hyperactive T cells and debilitated natural killer (NK) cell, respectively. Modeling and experiments showed that early IFN-g secretion predicted later differences in secreted profiles in vitro. This effect was recapitulated in healthy PBMCs by blocking the IFN-g receptor. Thus, we identified a critical deficiency in NK cell responses of HIV-infected individuals, independent of CD4(+) T cell depletion, which directs secreted profiles. Our findings illustrate a broad approach for identifying key disease-associated nodes in a multicellular, multivariate signaling network.